Basic scatterplot: use mode = "markers"

plot_ly(mtcars, x=mtcars$wt,y=mtcars$mpg, mode="markers")

plot_ly(mtcars, x=mtcars$wt,y=mtcars$mpg, mode="markers", color=as.factor(mtcars$cyl))

plot_ly(mtcars, x=mtcars$wt,y=mtcars$mpg, mode="markers", color=mtcars$disp)

Use variable hp to show the point

plot_ly(mtcars, x=mtcars$wt,y=mtcars$mpg, mode="markers", color=as.factor(mtcars$cyl),size=mtcars$hp)

set.seed(2016-07-21)
temp <- rnorm(100, mean=30, sd=5)
pressue <- rnorm(100)
dtime <- 1:100
plot_ly(x = temp, y=pressue, z=dtime, type="scatter3d", mode="markers", color=temp)

Ploting a time series dataset airmiles (see time(airmiles))

data("airmiles")
plot_ly(x=time(airmiles), y=airmiles, mode="lines")

data("EuStockMarkets")
stock <- as.data.frame(EuStockMarkets) %>% 
    gather(index, price) %>% 
    mutate(time = rep(time(EuStockMarkets),4))
plot_ly(stock, x = stock$time, y=stock$price, color=stock$index)

plot_ly(x = precip, type="histogram")

plot_ly(iris, y = iris$Petal.Length, color=iris$Species, type= "box")

Are useful for displaying three dimensional data in two dimensions, using color for the third dimension,

terrain1 <- matrix(rnorm(100*100),nrow=100, ncol=100)
plot_ly(z=terrain1, type= "heatmap")

terrain2 <- matrix(sort(rnorm(100*100)),nrow=100, ncol=100)
plot_ly(z=terrain2, type= "surface")

state_pop <- data.frame(State=state.abb, Pop=as.vector(state.x77[,1]))
state_pop$hover <- with(state_pop, paste(State,'<br>',"Population:", Pop))
borders <- list(color = toRGB("red"))
map_options <- list(
  scope = 'usa',
  projection = list(type = 'albers usa'),
  showlakes = TRUE,
  lakecolor = toRGB('white')
)
plot_ly(state_pop, z=state_pop$Pop, text = state_pop$hover, locations = state_pop$State, type= 'choropleth', locationmode = 'USA states', color=state_pop$Pop, colors= 'Blues', marker=list(line=borders)) %>% layout(title='US Population in 1975', geo=map_options)